Hyper-Personalization Is Key for Dutch E-commerce Player Wehkamp.nl

One of the first – and now, largest – e-commerce companies in the Netherlands, wehkamp.nl has tapped IBM to help the platform improve its marketing and dynamic-merchandising strategies. Using myriad IBM cloud products, including Digital Analytics, LIVEMail and Campaign, the e-retailer has noticed significant gain in click-through rates on banner ads (500%) and a 271% lift in its sales-per-send ratio on marketing emails.

ALEXANDER VAN SLOOTEN: Wehkamp.nl started as a mail-order company in 1952 and we are a very strong brand in the Netherlands that [went] online in 1995 as one of the first e-commerce companies in the Netherlands. Since 2004, the main part of our annual [business] comes through the online channel. In 2010, we stopped [operating] our print catalog and we are now 100% online. We have no physical stores and had 122 million visitors to our site last year. We sell in five different categories – fashion, living, electronics, beauty and wellness and sports and leisure. We’re very large in women’s fashion. Seventy-five percent of our customer base is female, and for the demographics, if you look at the age we serve, it’s 22-49; the average age is around 33-34.

How are you using IBM solutions to crack the code on customer data?

Our involvement with IBM came more or less [as a result] of IBM buying [many of] the products we use in the online channel. We started with Web analytics six or seven years ago, because we had to analyze everything that was happening on our website. We started using Coremetrics, and IBM bought Coremetrics. The first question that we as an online retailer had about the website is, how can we improve the customer journey and funnel? Why do people leave the checkout process? It was anything about optimizing and usability. We were in need of a very extensive Web analytics tool, so we chose Coremetrics.

The second product we bought was Tealeaf, because Web analytics show everything that’s happening on your site, but it doesn’t really show why it’s happening. You see things, but you keep asking yourself, “What exactly did this customer see on the site?” Using Tealeaf, an analyst in our marketing intelligence team can sit back and see all the pages that an individual customer has seen, including the error messages and any problems they had. It’s all used to optimize our website, so we use it for individual problems. We have a very complex checkout process with well over 100 different ways to get from the cart to the Thank You page. It’s almost impossible to monitor all those flows, so you have to have software that keeps an eye on all those flows in the checkout process. We have alerting in Tealeaf, for example, every time a customer does strange things in a specific flow. Maybe there’s a bug, or maybe we can try to solve it.

How have you used Criteo in conjunction with IBM's Coremetrics for remarketing purposes?

We track, for every visitor, what product he or she looks at. That data is used to display that specific product in display ads on another website. When I’m behind my computer and I’m looking at a [product] at this moment, I might browse the Internet this evening and go to a news page. The odds are a display ad will show up and show the exact product I looked at that afternoon combined with the products that are also relevant for that customer based on products that are often bought with the product, or that have been viewed in different sessions. Coremetrics has something called Intelligent Offer that predicts, or gives a list of products that are bundled together with the main product or have been viewed in the same session with that product, so it’s kind of a prediction that can be relevant for a customer looking at the display ad. The conversions are really good, as is the return on investment.

To improve your profitability when selling clearance items, do you “segment” the clearance customer vs. the full-price purchaser?

What we don’t do, yet, is use a different price for different customers, but we will be starting to use DemandTec, another product of IBM, in a few months. What it does for us is predict what price (a product needs to be) at a specific moment. You can imagine when a product is out of stock and we start to sell it on our site, it has a specific product lifecycle and if the product doesn’t get bought in the first month, we have to lower the price a little sooner than products that are faster moving. It helps us to determine the right price and right setting for a specific product. We have a lot of returns. People have two weeks to decide if they want to keep or return the product, and DemandTec has to keep in mind all the returns and base the new price setting based on all the products that will be returned.

What’s your mobile strategy?

We have a tablet app and, right now, 25% of our sales are from the mobile channel. About 24% come through the tablet, being our tablet app and optimized tablet website. Only 1% is through smartphones. When an offer is placed, we have to consider that the mobile channel is part of the customer journey. People use the smartphone to look at products, but to buy the product they switch to the desktop or tablet version. They’re not really buying on smartphones.

Does this have any bearing on ads?

No, it does not really, for us. On tablets, the display part is more or less the same as a desktop version and for displaying in apps, it’s not that large in the Netherlands, so mobile display ads are basically the same as the desktop version right now.

Where have you seen valuable ROI around your use of IBM products?

We used to basically send out the same mail to every single customer. But … now we know what products the customer has looked at and what products are relevant in combination to that product, and we can use it to personalize our email ... The trick is to be relevant to all individual customers and that’s quite hard when you have 1.7 million customers. You need solutions to collect data, build profiles, and you have to have email tooling that can use that data to personalize all those messages and promotions.

That 271% higher sales percent ratio is due to the fact that we have been able to send out more relevant emails to every customer we have a profile for.

Can you describe the inroads you’re making in personalization?

We personalize in email now, but we also want to do it on our website. For example, if you are of a customer of wehkamp.nl and we know you are size “x,” why do we show you products we don’t have in your size? You like a product, go to the product detail page, go to your size and if it’s not available, that’s really dissatisfying. So I can use all your data to optimize everything on our website. If I know you have a strong interest in certain brands, I will position those brands and promotions higher than other brands. The next step is to do what we’re already doing with email on our (online) platform and not just be serving one website, but dynamically building almost 2 million websites for each and every individual customer. That will also be done with the help of IBM, because the basic profile of our customer is in our system and we have a lot of data and a big data problem. But, as we see it, IBM will collect the data and build the profile in their system, and we come up with different tricks to use the data.